<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/34475?offset=30 https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler Fri, 04 May 2018 19:18:41 -0500 https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler <![CDATA[The MARVEL assembler]]> MARVEL consists of a set of tools that facilitate the overlapping, patching, correction and assembly of noisy (not so noisy ones as well) long reads.

The assembly process can be summarized as follows:

  1. overlap
  2. patch reads
  3. overlap (again)
  4. scrubbing
  5. assembly graph construction and touring
  6. optional read correction
  7. fasta file creation

Address of the bookmark: https://github.com/schloi/MARVEL

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly Mon, 18 May 2020 16:47:56 -0500 https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly <![CDATA[Genobuntu: Package for Next Generation Sequencing and Genome Assembly]]>

Genobuntu is a software package containing more than 70 software and packages oriented towards NGS. In its current version, Genobuntu supports pre assembly tools, genome assemblers as well as post assembly tools.

Commonly used biological software and example script files for different assembly pipelines have also been provided, where the example script files can be updated to suit one’s experimental needs. Genobuntu attempts to reduce the amount of time and energy needed to build software workstations and it can also act as a good teaching source for a class room setting.

Therefore, Genobuntu offers a well-tailored environment for both novices and experts working in the field of genome assembly.

Features

  • Velvet
  • MiB
  • SSAKE
  • EULER
  • VCAKE
  • ABySS
  • ALLPATHS
  • Celera
  • SHARCGS
  • Allpaths
  • IDBA
  • TAIPAN
  • Edena
  • SOAPdenovo
  • Maq
  • IDBA-UD
  • No. of Reads present in the Ref. Seq.
  • ART NGS Reads Simulator
  • HiTEC, FASTQC
  • Minimum Description Length
  • SOAPaligner
  • Sequencing Read Archive Toolkit

Address of the bookmark: https://sourceforge.net/projects/genobuntu/

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/38563/hecil-a-hybrid-error-correction-algorithm-for-long-reads-with-iterative-learning Tue, 01 Jan 2019 12:01:00 -0600 https://bioinformaticsonline.com/bookmarks/view/38563/hecil-a-hybrid-error-correction-algorithm-for-long-reads-with-iterative-learning <![CDATA[HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning]]> HECIL—Hybrid Error Correction with Iterative Learning—a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read alignments. 

HECIL’s core algorithm by introducing an iterative learning paradigm that enhances the correction policy at each iteration by incorporating knowledge gathered from previous iterations via data-driven confidence metrics assigned to prior corrections.

Address of the bookmark: https://github.com/NDBL/HECIL

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform Fri, 10 Aug 2018 13:29:28 -0500 https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform <![CDATA[FMLRC: a long-read error correction tool using the multi-string Burrows Wheeler Transform]]> FMLRC, or FM-index Long Read Corrector, is a tool for performing hybrid correction of long read sequencing using the BWT and FM-index of short-read sequencing data. Given a BWT of the short-read sequencing data, FMLRC will build an FM-index and use that as an implicit de Bruijn graph. Each long read is then corrected independently by identifying low frequency k-mers in the long read and replacing them with the closest matching high frequency k-mers in the implicit de Bruijn graph. In contrast to other de Bruijn graph based implementations, FMLRC is not restricted to a particular k-mer size and instead uses a two pass method with both a short "k-mer" and a longer "K-mer". This allows FMLRC to correct through low complexity regions that are computational difficult for short k-mers.

Address of the bookmark: https://github.com/holtjma/fmlrc

]]> Neel https://bioinformaticsonline.com/researchlabs/view/17501/nieduszynski-group Fri, 26 Sep 2014 19:35:06 -0500 <![CDATA[Nieduszynski Group]]> Complete, accurate replication of the genome is essential for life. All chromosomes in eukaryotic cells must be duplicated and then segregated to daughter cells to ensure genetic integrity and produce the large number of cells that make up a multicellular organism. We are using genetic, genomic and computational methods to understand how chromosome replication is regulated to ensure genome stability. By focusing on the basic biology that underpins cell growth and division we aim to provide new insights that may help our understanding of diseases such as cancer and congenital disorders.

More http://www.nieduszynski.org/index.php
http://www.path.ox.ac.uk/research/cell-biology-and-pathology/conrad-nieduszynski-group

]]> https://bioinformaticsonline.com/file/view/19560/alien-genome Sat, 13 Dec 2014 00:24:32 -0600 https://bioinformaticsonline.com/file/view/19560/alien-genome <![CDATA[Alien Genome !!!]]> Genome sequencing, analysis and expression of Alien genome.

Note: This image/cartoon is create only for fun. It has nothing to do with any scientific findings.

]]> Jit https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing Tue, 07 Jul 2015 16:59:25 -0500 https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing <![CDATA[Scaffolding of a bacterial genome using MinION nanopore sequencing]]> Second generation sequencing has revolutionized genomic studies. However, most genomes contain repeated DNA elements that are longer than the read lengths achievable with typical sequencers, so the genomic order of several generated contigs cannot be easily resolved. A new generation of sequencers offering substantially longer reads is emerging, notably the Pacific Biosciences (PacBio) RS II system and the MinION system, released in early 2014 by Oxford Nanopore Technologies through an early access program.

Address of the bookmark: http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html

]]> Rahul Agarwal https://bioinformaticsonline.com/bookmarks/view/36403/ngmlr-long-read-mapper-designed-to-align-pacbio-or-oxford-nanopore Wed, 25 Apr 2018 07:30:54 -0500 https://bioinformaticsonline.com/bookmarks/view/36403/ngmlr-long-read-mapper-designed-to-align-pacbio-or-oxford-nanopore <![CDATA[NGMLR: long-read mapper designed to align PacBio or Oxford Nanopore]]> CoNvex Gap-cost alignMents for Long Reads (ngmlr) is a long-read mapper designed to sensitively align PacBilo or Oxford Nanopore to (large) reference genomes. It was designed to quickly and correctly align the reads, including those spanning (complex) structural variations. Ngmlr uses an SV aware k-mer search to find approximate mapping locations for a read and then a banded Smith-Waterman alignment algorithm to compute the final alignment. Ngmlr uses a convex gap cost model that penalizes gap extensions for longer gaps less than for shorter ones to compute precise alignments. The gap model allows ngmlr to account for both the sequencing error and real genomic variations at the same time and makes it especially effective at more precisely identifying the position of breakpoints stemming from structural variations. The k-mer search helps to detect and split reads that cannot be aligned linearly, enabling ngmlr to reliably align reads to a wide range of different structural variations including nested SVs (e.g. inversions flanked by deletions).

Address of the bookmark: https://github.com/philres/ngmlr

]]> Jit https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads Tue, 27 Nov 2018 03:38:49 -0600 https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads <![CDATA[Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads]]> Deepbinner is a tool for demultiplexing barcoded Oxford Nanopore sequencing reads. It does this with a deep convolutional neural network classifier, using many of the architectural advances that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and Porechop), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.

  • Reasons to use Deepbinner:
    • To minimise the number of unclassified reads (use Deepbinner by itself).
    • To minimise the number of misclassified reads (use Deepbinner in conjunction with Albacore demultiplexing).
    • You plan on running signal-level downstream analyses, like Nanopolish. Deepbinner can demultiplex the fast5 fileswhich makes this easier.
  • Reasons to not use Deepbinner:
    • You only have basecalled reads not the raw fast5 files (which Deepbinner requires).
    • You have a small/slow computer. Deepbinner is more computationally intensive than Porechop.
    • You used a sequencing/barcoding kit other than the ones Deepbinner was trained on.

Address of the bookmark: https://github.com/rrwick/Deepbinner

]]> Neel https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology Tue, 19 Dec 2017 18:49:28 -0600 https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology <![CDATA[1mb long DNA with Nanopore technology]]> The first continuous DNA read of more than a million bases (>1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO

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